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Finding Approximate Analytic Solutions To Differential Equations Using Genetic Programming

机译:利用遗传规划求微分方程的近似解析解

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The computational optimization technique, genetic programming, is applied to the analytic solution of general differential equations. The approach generates a mathematical expression that is an approximate or exact solution to the particular equation under consideration. Angeline's module acquisition (MA) and Koza's automatically defined functions (ADF) are considered and the results of some modifications are presented, including a significant result regarding a generalized crossover operator.

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